The present invention relates in general to the field of silicon wafer processing, and more particularly, to an apparatus and method for automating the detection of defects in individual silicon chips.
Without limiting the scope of the invention, its background is described in connection with the processing of silicon chips on silicon wafers, such as dynamic random access memory (DRAM), as an example.
Heretofore, in this field, the detection of defects on silicon wafers within individual silicon chips has been performed either manually, or using automated visual systems having a defect detection resolution of 2-4 microns. Unfortunately, the accuracy of detection in many cases was limited by the operator""s ability to view a random sample of conventional silicon dies within a specified period of time.
Conventional automated systems have achieved up to a 90% success rate in detecting silicon wafers surface anomalies. These success rates, however, were achieved only under the best conditions of light and contrast. Importantly, reliability of conventional automated systems has been found to degrade rapidly if conditions of lighting and contrast are not ideal.
Furthermore, the limitations of current methods for automatically inspecting silicon dies for defects require substantial visual inspection by an operator. For example, the field of view of present systems is limited to one die, thereby excluding from analysis up to 60% of the available 2.56 kilobytes of data obtained from a field of view of 125xc3x97150 mils. This field of view limits spacial accuracy to about 1:16, with a sub-pixel alignment of 0.25. The problem of the limited field of view of present systems is exacerbated by the inherent difference in the lighting and contrast of the underlying silicon wafer background. The inability of present systems to cope with differences in lighting and contrast is a major stumbling block to further automation of silicon die analysis because differences in wafer background are found to occur even between different silicon wafer lots for the same type of silicon chip.
What is needed is an automated imaging system that is truly automatic and customizable for each silicon wafer processed. Also needed is an automated system that adjusts to the intrinsic differences in lighting and contrast of each silicon wafer. A need has also arisen for an automatic inspection system that is able to adapt to different silicon chip patterns, and that accurately detects surface defects on silicon dies on a silicon wafer. A need has further arisen for a system that is able to meet the needs of high throughput without a loss of accuracy. Finally, a need has arisen for an automated system that is able to adapt to the high precision needs of future silicon chip designs.
The present invention disclosed herein is an apparatus and method for automatically detecting defects on silicon dies on a silicon wafer. The apparatus for automatically detecting defects on silicon dies comprises an image acquisition system and a computer connected to the image acquisition system. The computer automatically calibrates the focal plane and/or the lighting of the image acquisition system. Next, the computer analyzes a random sample of silicon dies to determine an average or standardized die image. Finally, the statistical die model is compared to silicon dies on a silicon wafer to determine if the silicon dies have surface defects.
The apparatus for automatically detecting defects on silicon dies on a silicon wafer, in one embodiment, aligns the silicon wafer based on alignment dies. The apparatus physically aligns the silicon wafer by, for example, using an automated wafer handling system to position the silicon wafer in alignment with the image acquisition system. The image acquisition system can further include a high resolution microscope, which may be connected to a display unit that displays an image of the surface of silicon dies.
The apparatus for automatically detecting defects on silicon dies on a silicon wafer of the present invention can further include a wafer identification (wafer ID) reader that provides the computer with information about the silicon wafer. The computer of the present invention can also be connected to a display unit that displays an image that represents the silicon wafer acquired by the image acquisition system. The display unit of the present invention can be, for example, a touch screen cathode ray tube that permits input from the screen to the computer.
The display unit can display a summary of the results from comparing the statistical die model with the silicon dies. The image acquisition system of the present invention may further comprise a wafer cassette that provides the wafer handling system with silicon wafers.
The present invention also encompassed a method for automatically detecting defects in silicon dies on a silicon wafer comprising the steps of, automatically aligning a silicon wafer, calibrating the focal plane of an image acquisition system, adjusting the lighting conditions of the image acquisition system, identifying a random sample of silicon dies on the surface of the silicon wafer, calculating a statistical die model from the random sample, determining if the silicon dies have surface defects and displaying the results of the comparison. The results of the comparison can be compiled into a list of silicon dies that were found to be defective when compared to the statistical die model. The results of the comparison can also be compiled into a list of silicon dies that were found to be correct. The present invention also encompassed a method for automatically detecting defects on silicon dies, wherein the list of defective dies may be displayed graphically on a display unit as a representation of a silicon wafer. The list can also be printed or stored in a computer memory, or on a storage medium.